Estimating the Size of an Open Population with Massive Datasets Based on a Generalized Varying-Coefficient Model

A generalized varying-coefficient model is proposed to estimate a population size at a specific time from multiple lists of an open population. The research datasets have millions of records with a very long time span (38 years), bringing challenges to calculations. The authors develop a regularization iterative algorithm to overcome this difficulty. The asymptotic distribution of the proposed estimators is derived. Simulation studies show that the procedure works well. The method is applied to estimate the number of drug abusers in Hong Kong, China over the period 1977–2014.